How to use the nyoka.Base64.FloatBase64.from_floatArray function in nyoka

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github nyoka-pmml / nyoka / nyoka / PMML44 / wrapper44.py View on Github external
self.biasShape = supermod._cast(None, biasShape)
        self.biasFlattenAxis = supermod._cast(None, biasFlattenAxis)
        self.src = supermod._cast(None, src)
        if Extension is None:
            self.Extension = []
        else:
            self.Extension = Extension
        if mixedclass_ is None:
            self.mixedclass_ = supermod.MixedContainer
        else:
            self.mixedclass_ = mixedclass_
        validFloatTypes = ["float6", "float7", "float8", "float16", "float32", "float64"]
        if floatType not in validFloatTypes:
            floatType = "float32"
        from nyoka.Base64 import FloatBase64
        base64string = "\t\t\t\t" + "data:" + floatType + ";base64," + FloatBase64.from_floatArray(content, floatsPerLine)
        base64string = base64string.replace("\n", "\n\t\t\t\t")
        self.content_ = [supermod.MixedContainer(1, 2, "", base64string)]
        self.valueOf_ = base64string
github nyoka-pmml / nyoka / nyoka / PMML44 / wrapper44.py View on Github external
self.weightsShape = supermod._cast(None, weightsShape)
        self.weightsFlattenAxis = supermod._cast(None, weightsFlattenAxis)
        self.src = supermod._cast(None, src)
        if Extension is None:
            self.Extension = []
        else:
            self.Extension = Extension
        if mixedclass_ is None:
            self.mixedclass_ = supermod.MixedContainer
        else:
            self.mixedclass_ = mixedclass_
        validFloatTypes = ["float6", "float7", "float8", "float16", "float32", "float64"]
        if floatType not in validFloatTypes:
            floatType = "float32"
        from nyoka.Base64 import FloatBase64
        base64string = "\t\t\t\t" + "data:" + floatType + ";base64," + FloatBase64.from_floatArray(content, floatsPerLine)
        base64string = base64string.replace("\n", "\n\t\t\t\t")
        self.content_ = [supermod.MixedContainer(1, 2, "", base64string)]
        self.valueOf_ = base64string